Gen AI Engineer

About the job

• Collect and prepare data for training and evaluating multimodal foundation models. This may involve cleaning and processing text data or creating synthetic data. • Develop and optimize large-scale language models like GANs (Generative Adversarial Networks) and VAEs (Variational Autoencoders) • Work on tasks involvin ... g language modeling, text generation, understanding, and contextual comprehension. • Regularly review and fine-tune Large Language models to ensure maximum accuracy and relevance for custom datasets. • Build and deploy AI applications on cloud platforms – any hyperscaler Azure, GCP or AWS. • Integrate AI models with our company's data to enhance and augment existing applications. Role & Responsibility • Handle data preprocessing, augmentation, and generation of synthetic data. • Design and develop backend services using Python or .NET to support OpenAI-powered solutions (or any other LLM solution) • Develop and Maintaining AI Pipelines • Work with custom datasets, utilizing techniques like chunking and embeddings, to train and fine-tune models. • Integrate Azure cognitive services (or equivalent platform services) to extend functionality and improve AI solutions • Collaborate with cross-functional teams to ensure smooth deployment and integration of AI solutions. • Ensure the robustness, efficiency, and scalability of AI systems. • Stay updated with the latest advancements in AI and machine learning technologies. Skills & Experience · Strong foundation in machine learning, deep learning, and computer science. · Expertise in generative AI models and techniques (e.g., GANs, VAEs, Transformers). · Experience with natural language processing (NLP) and computer vision is a plus. · Ability to work independently and as part of a team. · Knowledge of advanced programming like Python, and especially AI-centric libraries like TensorFlow, PyTorch, and Keras. This includes the ability to implement and manipulate complex algorithms fundamental to developing generative AI models. · Knowledge of Natural language processing (NLP) for text generation projects like text parsing, sentiment analysis, and the use of transformers like GPT (generative pre-trained transformer) models. · Experience in Data management, including data pre-processing, augmentation, and generation of synthetic data. This involves cleaning, labeling, and augmenting data to train and improve AI models. · Experience in developing and deploying AI models in production environments. • Knowledge of cloud services (AWS, Azure, GCP) and understanding of containerization technologies like Docker and orchestration tools like Kubernetes for deploying , managing and scaling AI solutions • Should be able to bring new ideas and innovative solutions to our clients

Requirements

• machine learning
• deep learning
• computer science
• generative AI models
• NLP
• Python
• TensorFlow
• PyTorch
• Keras
• AI application deployment

Preferred Technologies

• machine learning
• deep learning
• computer science
• generative AI models
• NLP
• Python
• TensorFlow
• PyTorch
• Keras
• AI application deployment